Explainable Artificial Intelligence for Medical Data Analytics and Healthcare Applications | 79.42 MB
Title: Explainable Artificial Intelligence for Medical Data Analytics and Healthcare Applications
Author: Ganesh R Naik
Category: Nonfiction, Science & Nature, Technology, Imaging Systems, Engineering, Computers, General Computing
Language: English | 322 Pages | ISBN: 9781003810605
Description:
Since its first appearance, artificial intelligence has been ensuring revolutionary outcomes in the context of real-world problems. At this point, it has strong relations with biomedical and today's intelligent systems compete with human capabilities in medical tasks. However, advanced use of artificial intelligence causes intelligent systems to be black-box. That situation is not good for building trustworthy intelligent systems in medical applications. For a remarkable amount of time, researchers have tried to solve the black-box issue by using modular additions, which have led to the rise of the term: interpretable artificial intelligence. As the literature matured (as a result of, in particular, deep learning), that term transformed into explainable artificial intelligence (XAI).
This book provides an essential edited work regarding the latest advancements in explainable artificial intelligence (XAI) for biomedical applications. It includes not only introductive perspectives but also applied touches and discussions regarding critical problems as well as future insights.
Topics discussed in the book include:
- XAI for the applications with medical images
- XAI use cases for alternative medical data/task
- Different XAI methods for biomedical applications
- Reviews for the XAI research for critical biomedical problems.
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